E learning állás, munka

• Learning existing system architecture, codebase, tools, and development practices
• Validating existing technical documentation and flagging any gaps or outdated content
• Highlighting blockers to knowledge transfer such as missing info, unclear logic, inaccessible systems

• Leading a data engineering team comprising 5-6 consultants
• Overseeing project delivery
• Managing and mentoring the team
• Ensuring successful execution of data engineering projects
• Ensuring successful execution of ML and MLOps projects
• Ensuring successful execution of cloud migration projects

• Backend and frontend development with focus on high-performance and speed
• Cooperation with product team including UX, UI, and product management
• Building and coding backend in Node.JS and frontend in React in a complex web application
• Participation in and conducting code reviews

• Maintaining and evolving data structures
• Building new ETL flows and maintaining or improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods

• Development and customization of Microsoft Dynamics 365 applications using C#/.NET and Power Platform tools
• Building integrations between Dynamics 365 and Azure services such as Logic Apps and Functions

• Design and implement core authentication and authorization including POST /auth/token endpoint, JWT validation middleware, and entitlement enforcement layer
• Build and maintain entitlement decision cache with invalidation on entitlement changes

Development and enhancement of the MSCI Index Development Platform and the IndexMetrics Real-Time application using modern software engineering practices, Python, Azure, and AI-assisted development tools...

Design, develop, test, document, and deploy high quality Salesforce solutions leveraging the latest capabilities of the Einstein 1 Platform, Lightning Web Components, and modern Apex patterns...

• Delivery on complex projects individually or by leading small delivery teams
• Management of customer relationships alone or in collaboration with a Project Manager
• Support of pre-sales process
• Mentoring of more junior engineers
• Contribution to hiring best-in-class data talent

• Design of Azure cloud infrastructure to support Databricks and data platform workloads
• Implementation of Azure cloud infrastructure to support Databricks and data platform workloads
• Management of Azure cloud infrastructure to support Databricks and data platform workloads

• Complex programming, testing and debugging functions related to the implementation of SAP modules
• Understanding requirements from provided functional designs and transforming them into technical designs
• Keeping contact with clients, functional teams, and designers

• Delivery of complex data engineering projects individually or by leading small delivery teams
• Management of customer relationships alone or in collaboration with a Project Manager
• Support of pre-sales process
• Mentoring of more junior engineers
• Contribution to hiring best-in-class data talent

• Delivery on complex data engineering projects across industries
• Leading small delivery teams
• Managing customer relationships alone or with a Project Manager
• Mentoring more junior engineers
• Evaluating the quality of junior engineers' work
• Contributing to hiring best-in-class data engineers

• Contribution to Customer Platform team
• Delivery of high-quality NodeJS, TypeScript and React code with simplicity, performance, and scalability
• Design and implementation of client and database-related application features

• Technical consultation and client education
• Creation of feasible delivery plans for on-time, on-budget, and high-quality project implementations
• Design and implementation of high-performing, maintainable, and secure software aligned with industry best practices and company capabilities

• Ownership of data models and storage architecture behind AI systems across relational, graph, and retrieval-oriented data
• Building and operating APIs, backend services, and pipelines to keep data current and accessible

• Build and operate deployment pipelines for AI services covering CI/CD, infrastructure-as-code, environment promotion, and rollback
• Deploy and operate model serving, batch scoring, and orchestration pipelines across development, staging, and production

• Design and implement data fabric architecture across heterogeneous data sources and platforms
• Develop scalable ETL/ELT pipelines for batch and real-time data integration
• Integrate structured and unstructured data from databases, APIs, SaaS applications, data lakes, and enterprise systems

• Ownership and evolution of Tulip’s Cypress + TypeScript E2E automation framework
• Integration of automated test suites into CI/CD pipelines
• Research and implementation of load and performance testing strategies
• Application of AI-assisted tools to accelerate test generation and triage failures

• Contribution to ID Verification team as an essential part of fraud prevention solution
• Delivery of high-quality NodeJS, TypeScript and React code with simplicity, performance, and scalability
• Design and implementation of cutting edge client and database-related application features